PROJECT SUMMARY In response to RFA-HD-15-009 for the Population Dynamics Centers Research Infrastructure FY 2015 (P2C), the University of Colorado at Boulder Population Center (CUPC) requests five years of funding from NICHD for infrastructure support. With its first center award in 2010, CUPC made substantial progress in the size and quality of the faculty affiliates, the number of external grants, and its professional presence and scholarly influence in population research. With continued center funding, we propose to build on this progress with innovative work in our primary research areas; collaborative ties across disciplines; institutional ties with colleagues in other universities and nations; mentoring and support for a group of promising junior faculty; center support for excellence in population science research; and increased external funding. Toward these goals, the proposal describes the three primary research areas of the center: health and mortality; migration and spatial demography; and environmental demography. It also describes plans to scale up funding support, advance several new research initiatives, target novel and significant research with center funding, and bring in scholars with new expertise and shared interests in population topics. The activities all aim to increase the pace and impact of center research. The center requests three infrastructure cores: The Administrative Core provides crucial services to all affiliates, including clerical, bibliographic, editing, and grants management support for research projects. The Development Core provides seed awards to allow researchers ? particularly junior affiliates ? to begin and develop innovative research and improve chances for external funding. It further provides leadership for several new initiatives that expand our primary research areas. The Scientific/Technical (or Data) Core deals with issues relating to the access, management, processing, and analysis of data. It supports a first-rate computing and technology environment for handling large and complex data sets and makes use of affiliate expertise for statistical training and consultation.